Acoustic emotion recognition two ways of features selection based on self-adaptive multi-objective genetic algorithm
Acoustic emotion recognition two ways of features selection based on self-adaptive multi-objective genetic algorithm
复制标题
基于自适应多目标遗传算法的声音情感识别两种特征选择方式
DOI：
10.5220/0005148708510855
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
E. Semenkin
中科院分区：
文献类型：
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作者：
C. Brester;M. Sidorov;E. Semenkin
本文在基于语音的情感识别问题（英语、德语）上研究了基于进化多目标优化算法的特征选择技术的效率。与所涉及数据库的主成分分析相比，证明了开发的算法方案的优点。所提出的方法不仅可以减少分类器使用的特征量，还可以提高其性能。根据获得的结果，使用所提出的技术可能会导致情绪识别准确率相对提高高达 29.37%，并将某些语料库的特征数量从 384 个减少到 64.8 个。
In this paper the efficiency of feature selection techniques based on the evolutionary multi-objective optimization algorithm is investigated on the set of speech-based emotion recognition problems (English, German languages). Benefits of developed algorithmic schemes are demonstrated compared with Principal Component Analysis for the involved databases. Presented approaches allow not only to reduce the amount of features used by a classifier but also to improve its performance. According to the obtained results, the usage of proposed techniques might lead to increasing the emotion recognition accuracy by up to 29.37% relative improvement and reducing the number of features from 384 to 64.8 for some of the corpora.
(2007)“阿尔斯特爱尔兰语不定式从句摘录”。
DOI：
--
发表时间：
2007
期刊：
In Proceedings of the 135th Meeting of the Linguistic Society of Japan
影响因子：
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作者：
O Baoill;Donall P. and Hideki Maki
通讯作者：
Donall P. and Hideki Maki